Abstract

A catalytic - DBD plasma reactor was designed and developed for co-generation of synthesis gas and C2+ hydrocarbons from methane. A hybrid Artificial Neural Network - Genetic Algorithm (ANN-GA) was developed to model, simulate and optimize the reactor. Effects of CH4/CO2 feed ratio, total feed flow rate, discharge voltage and reactor wall temperature on the performance of catalytic DBD plasma reactor was explored. The Pareto optimal solutions and corresponding optimal operating parameters ranges based on multi-objectives can be suggested for catalytic DBD plasma reactor owing to two cases, i.e. simultaneous maximization of CH4 conversion and C2+ selectivity, and H2 selectivity and H2/CO ratio. It can be concluded that the hybrid catalytic DBD plasma reactor is potential for co-generation of synthesis gas and higher hydrocarbons from methane and carbon dioxide and showed better than the conventional fixed bed reactor with respect to CH4 conversion, C2+ yield and H2 selectivity for CO2 OCM process.